This invention relates to automatic climate control systems for vehicles, and more particularly to a method of generating control system algorithms that optimize occupant comfort.
In an automotive automatic climate control system (ACCS), the driver generally selects a desired cabin temperature, and a microprocessor-based system controller responds in a pre-programmed way to control the blower speed, the air discharge temperature and the air delivery mode. While the driver has the option of overriding the pre-programmed settings, the objective is to design the control algorithms so that the pre-programmed settings sufficiently satisfy the occupants that little or no overriding is necessary. This presents a very difficult challenge to system and calibration engineers because control settings that satisfy the engineers may only satisfy a small subset of the overall population of vehicle occupants. For this reason, and in order to reduce development time, there has been a trend toward increased usage of math-based tools to simulate and analyze system operation, and to compare the performance achieved with different system designs and control approaches. See, for example, the U.S. Patent to Webster et al. U.S. Pat. No. 6,209,794, where mathematical models of a vehicle and thermal management system are utilized to evaluate the impact of different system designs on the time required for the cabin to reach a comfortable temperature.
While math-based tools have the capability of accelerating the validation process and significantly reducing product development time, the fact remains that it is difficult to develop control strategies that satisfactorily address occupant comfort. Even in cases where occupant comfort standards are reasonably well defined, many design iterations are required to develop a control algorithm that will satisfy the defined comfort standards. Accordingly, what is needed is an improved method of applying math-based tools to the control algorithm design process that minimizes the number of design iterations required to arrive at a solution that optimizes occupant comfort.
The present invention is directed to an improved method of developing optimized control algorithms for a vehicular automatic climate control system (ACCS). According to the invention, math-based models are utilized to simulate the vehicle, the ACCS and the occupant, and the models are cross-coupled in closed-loop fashion with feedback from both vehicle and occupant. A first feedback loop including the vehicle and the ACCS simulates how the ACCS interacts with the cabin environment; and a second feedback loop including the vehicle, the ACCS and the occupant simulates how the occupant will adjust the ACCS to optimize comfort. When the control algorithm satisfies the control objectives and optimizes occupant comfort, an auto-code generation tool is used to create program code directly from the control model, which may be downloaded into a test vehicle for final system confirmation and calibration.